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Impact of ambient temperature on hospital admissions for respiratory diseases in suburban rural villages in northwest China

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Abstract

Extreme temperature is strongly associated with human health, but few studies are available for the effects of extreme temperatures on respiratory disease (RD) in rural villages in Jiuquan, China over 2018–2019. In this study, we evaluate the effect of daily mean temperature on RD hospitalizations in suburban rural villages. A distribution lag non-linear model was constructed to analyze the relationship between the temperature and the daily risk of RD hospitalizations; and stratified analysis by sex and age group was performed. The effect of daily mean temperature on RD hospitalizations was non-linear and lagging. With a reference 25th percentile of temperature (−1.8 °C), exposure to extremely low temperature (−15.8 °C, 1st percentile), or moderate low temperature (−8.3 °C, 10th percentile) were associated with 1.396 (95% CI: 1.251, 1.558) and 1.216 (95% CI: 1.180, 1.253) increased risks of RD hospitalizations over lag 0–21 days. For RD morbidity, the effects of moderate high temperature (90th percentile of temperature, 22.5 °C) appeared at on the exposed day (lag 0), with the largest hot effect (RR 1.008, 95% CI 1.001, 1.020), while the effects of extremely high temperature (99th percentile of temperature, 27.0 °C) were insignificant. The effect of ambient temperature varied with gender and age. Both cold and high temperatures have more serious influence on males than females. In contrast, the elderly (age ≥ 65) seemed to be more sensitive in extremely low temperature (RR = 3.471; 95% CI, 2.183, 5.518; lag 0–21). The effect of moderate high temperature on the < 65 years group appeared for the first time at lag 0 (RR = 1.012; 95% CI, 1.001, 1.029). Both high temperature and low temperature increased the RD hospitalization risk; the harmful effect and duration of low temperature were greater than that of high temperature; the ≥ 65-year group and male were more sensitive to low temperature.

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Data Availability

The datasets generated and/or analyzed during the current study are not publicly available due to confidentiality agreements but are available from the corresponding author on reasonable request.

Abbreviations

RD:

respiratory disease

DLNM:

distributed lag non-linear model

GAM:

generalized additive model

Q-AIC:

quasi-Poisson Akaike information criteria

RR:

relative risk

GHSD:

Gansu healthcare security administration

HIS:

hospital information system

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Funding

This study was supported by the National Natural Science Foundation of China (71861026) and the Natural Science Foundation of Gansu Province, China (Grant No. 21JR7RA864).

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Authors and Affiliations

  1. Jiayuguan Center for Disease Prevention and Control, Jiayuguan, 735100, China

    Shixiong Li

  2. School of Public Health, Lanzhou University, Lanzhou, 730000, China

    Shixiong Li & Jiyuan Dong

Authors
  1. Shixiong Li
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  2. Jiyuan Dong
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Contributions

Jiyuan Dong contributed to the conception or design of the work. Shixiong Li contributed to the acquisition, analysis, or interpretation of data for the work. Shixiong Li drafted the manuscript. Jiyuan Dong critically revised the manuscript. All gave final approval and agreed to be accountable for all the aspects of the work ensuring integrity and accuracy.

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Correspondence to Jiyuan Dong.

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The present study is considered exempt from institutional review board approval, since the data used was collected for administrative purpose without any personal identifiers.

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Not applicable.

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The authors declare no competing interests.

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Responsible Editor: Lotfi Aleya

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Shixiong Li and Jiyuan Dong are the co-first author.

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Li, S., Dong, J. Impact of ambient temperature on hospital admissions for respiratory diseases in suburban rural villages in northwest China. Environ Sci Pollut Res 29, 66373–66382 (2022). https://doi.org/10.1007/s11356-022-20446-0

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  • DOI: https://doi.org/10.1007/s11356-022-20446-0

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